Demo Data from EDBT 2026 / reviewers in the wild / expert
Christopher Neal Hinds
dblp:205/4231 · also Chris N. Hinds
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-1223-3747ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Processor architecture and microarchitecture · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Processor architecture and microarchitecture
instruction set architecture |
0.4 | 1 | 2019 | High-Precision Anchored Accumulators for Reproducible Floating-Point Summation · IEEE Trans. Computers 2019 |
Processor architecture and microarchitecture › instruction set architecture
vector extension |
0.4 | 1 | 2019 | High-Precision Anchored Accumulators for Reproducible Floating-Point Summation · IEEE Trans. Computers 2019 |
Mathematical optimization › numerical computation
floating-point arithmetic |
0.4 | 1 | 2019 | High-Precision Anchored Accumulators for Reproducible Floating-Point Summation · IEEE Trans. Computers 2019 |
Mathematical optimization
numerical analysis |
0.4 | 1 | 2019 | High-Precision Anchored Accumulators for Reproducible Floating-Point Summation · IEEE Trans. Computers 2019 |
Processor architecture and microarchitecture
instruction-level optimization |
0.1 | 1 | 2019 | High-Precision Anchored Accumulators for Reproducible Floating-Point Summation · IEEE Trans. Computers 2019 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | High-Precision Anchored Accumulators for Reproducible Floating-Point SummationabstractThis paper introduces a new datatype, the High-Precision Anchored (HPA) number, that allows reproducible accumulation of floating-point (FP) numbers in a programmer-selectable range. The new datatype has a larger significand and a smaller range than existing FP formats and has much better arithmetic and computational properties. In particular, it is associative, parallelizable, reproducible and correct. The paper also describes how HPA processing can be implemented as part of Arm's new Scalable Vector Extension (SVE) together with proposals for new instructions aimed specifically at the new datatype. For the modest ranges that will accommodate most problems, HPA processing is much faster than FP arithmetic: performance modelling shows 2-lane HPA accumulation of FP64 operands is 9.5 times faster on Arm's new vector architecture than double double accumulation and accelerates a recently published software algorithm for 3-lane reproducible FP summation by a factor of 5.6. This paper also discusses instruction-level optimizations for FP32 and FP16 summations that further increase HPA performance relative to FP64 accumulations. Neil Burgess, Christopher E. Goodyer, Christopher Neal Hinds, David Raymond Lutz |
IEEE Trans. Computers | 3 |
| 2017 | High-Precision Anchored Accumulators for Reproducible Floating-Point SummationabstractThis paper introduces a new datatype that allows reproducible accumulation of floating-point (FP) numbers in a programmer-selectable range. The new datatype has a larger significand and a smaller range than existing FP formats and has much better arithmetic and computational properties. In particular, it is associative, parallelizable, reproducible and correct. For the modest ranges that will accommodate most problems, it is also much faster: 3 to 12 times faster on a single 256-bit SIMD implementation. The paper also describes a new instruction and associated datapath that support the proposed datatype, and discusses how a recently published software algorithm for reproducible FP summation could be implemented using the proposed approach. David Raymond Lutz, Christopher Neal Hinds |
ARITH | 2 |
| 2007 | Design of the ARM VFP11 Divide and Square Root Synthesisable MacrocellabstractThis paper presents the detailed design of the ARM VFP11 divide and square root synthesisable macrocell. The macrocell was designed using the minimum-redundancy radix-4 SRT digit recurrence algorithm, and this paper describes a novel acceleration technique employed to achieve the required processor clock frequency of up to 750 MHz in 90 nm CMOS. Logical effort theory is used to provide a delay analysis of the unit, which demonstrates the balanced nature of the two critical paths therein. Neil Burgess, Christopher Neal Hinds |
IEEE Symposium on Computer Arithmetic | 2 |